CodeInvasion

I don’t know why you are mentioning Starship when I made no mention of that. Starship HLS is also a dumb idea, but that’s beside the point.

SLS is horribly expensive for what it provides.

The Defense Production Act could be used to meet these ends. SpaceX is a defense contractor and exists at the privilege of the US Government for the US Government.

Coming from several people who work with SpaceX, there is a dedicated group of people that exist to distract Elon from all vital SpaceX functions.

SLS is on track to be more expensive when adjusted for inflation per moon mission than the Apollo program. It is wildly too expensive, and should be cancelled.

This coupled with the fact that the rocket is incapable of sending a manned capsule to low earth orbit which is the the lunar gateway is planned to a Rectilinear Halo Orbit instead.

Those working in the space industry know that SpaceX’s success is not because of Elon but instead Gwynne Shotwell. She is the President and CEO of SpaceX and responsible for all things SpaceX. The best outcome after the election is to remove Elon from the board and revoke his ownership of what is effectively a defense company for political interference in this election. Employees at SpaceX would be happy, the government would be happy, and the American people would be happy.

The technical definition of AI in academic settings is any system that can perform a task with relatively decent performance and do so on its own.

The field of AI is absolutely massive and includes super basic algorithms like Dijsktra’s Algorithm for finding the shortest path in a graph or network, even though a 100% optimal solution is NP-Complete, and does not yet have a solution that is solveable in polynomial time. Instead, AI algorithms use programmed heuristics to approximate optimal solutions, but it’s entirely possible that the path generated is in fact not optimal, which is why your GPS doesn’t always give you the guaranteed shortest path.

To help distinguish fields of research, we use extra qualifiers to narrow focus such as “classical AI” and “symbolic AI”. Even “Machine Learning” is too ambiguous, as it was originally a statistical process to finds trends in data or “statistical AI”. Ever used excel to find a line of best fit for a graph? That’s “machine learning”.

Albeit, “statistical AI” does accurately encompass all the AI systems people commonly think about like “neural AI” and “generative AI”. But without getting into more specific qualifiers, “Deep Learning” and “Transformers” are probably the best way to narrow down what most people think of when they here AI today.

This is truly a terrible accident. Given the flight tracking data and the cold, winter weather at the time, structural icing is likely to have caused the crash.

Ice will increase an aircraft’s stall speed, and especially when an aircraft is flown with autopilot on in icing conditions, the autopilot pitch trim can end up being set to the limits of the aircraft without the pilots ever knowing.

Eventually the icing situation becomes so severe that the stall speed of the ice-laden wing and elevator exceeds the current cruising speed and results in a aerodynamic stall, which if not immediately corrected with the right control inputs will develop into a spin.

The spin shown in several videos is a terrifying flat spin. Flat spins develop from normal spins after just a few rotations. It’s very sad and unfortunate that we can hear that both engines are giving power while the plane is in a flat spin towards the ground. The first thing to do when a spin is encountered is to eliminate all sources of power as this will aggravate a spin into a flat spin.

Once a flat spin is encountered, recovery from that condition is not guaranteed, especially in multi-engine aircraft where the outboard engines create a lot of rotational inertia.

Valve is a unique company with no traditional hierarchy. In business school, I read a very interesting Harvard Business Review article on the subject. Unfortunately it’s locked behind a paywall, but this is Google AI’s summary of the article which I confirm to be true from what I remember:

According to a Harvard Business Review article from 2013, Valve, the gaming company that created Half Life and Portal, has a unique organizational structure that includes a flat management system called "Flatland". This structure eliminates traditional hierarchies and bosses, allowing employees to choose their own projects and have autonomy. Other features of Valve's structure include: 

• Self-allocated time: Employees have complete control over how they allocate their time 
• No managers: There is no managerial oversight 
• Fluid structure: Desks have wheels so employees can easily move between teams, or "cabals" 
• Peer-based performance reviews: Employees evaluate each other's performance and stack rank them 
• Hiring: Valve has a unique hiring process that supports recruiting people with a variety of skills

Someone did the math and realized we would need a 130% tariff on all goods to replace current income tax revenue.

People’s number one concern is inflation. If that tariff is created we will see 100% inflation over night!

You do realize that every posted on the Fediverse is open and publicly available? It’s not locked behind some API or controlled by any one company or entity.

Fediverse is the Wikipedia of encyclopedias and any researcher or engineer, including myself, can and will use Lemmy data to create AI datasets with absolutely no restrictions.

It took Hawking minutes to create some responses. Without the use of his hand due to his disease, he relied on the twitch of a few facial muscles to select from a list of available words.

As funny as it is, that interview, or any interview with Hawkins contains pre-drafted responses from Hawking and follows a script.

But the small facial movements showing his emotion still showed Hawking had fun doing it.

When I go back to being a Beltway Bandit, I need to remember these!

To add to this insight, there are many recent publications showing the dramatic improvements of adding another modality like vision to language models.

While this is my conjecture that is loosely supported by existing research, I personally believe that multimodality is the secret to understanding human intelligence.